OBJECTIVE: To examine the use of a submaximal exercise test in detecting change in fitness level after a physical training program, and to investigate the correlation of outcomes as measured submaximally or maximally.DESIGN: A prospective study in which exercise testing was performed before and after training intervention.SETTING: Academic and general hospital and rehabilitation center.PARTICIPANTS: Cancer survivors (N=147) (all cancer types, medical treatment completed > or =3 mo ago) attended a 12-week supervised exercise program.INTERVENTIONS: A 12-week training program including aerobic training, strength training, and group sport.MAIN OUTCOME MEASURES: Outcome measures were changes in peak oxygen uptake (Vo(2)peak) and peak power output (both determined during exhaustive exercise testing) and submaximal heart rate (determined during submaximal testing at a fixed workload).RESULTS: The Vo(2)peak and peak power output increased and the submaximal heart rate decreased significantly from baseline to postintervention (P<.001). Changes in submaximal heart rate were only weakly correlated with changes in Vo(2)peak and peak power output. Comparing the participants performing submaximal testing with a heart rate less than 140 beats per minute (bpm) versus the participants achieving a heart rate of 140 bpm or higher showed that changes in submaximal heart rate in the group cycling with moderate to high intensity (ie, heart rate > or =140 bpm) were clearly related to changes in VO(2)peak and peak power output.CONCLUSIONS: For the monitoring of training progress in daily clinical practice, changes in heart rate at a fixed submaximal workload that requires a heart rate greater than 140 bpm may serve as an alternative to an exhaustive exercise test.
Background: The emergence of smartphones and wearable sensor technologies enables easy and unobtrusive monitoring of physiological and psychological data related to an individual’s resilience. Heart rate variability (HRV) is a promising biomarker for resilience based on between-subject population studies, but observational studies that apply a within-subject design and use wearable sensors in order to observe HRV in a naturalistic real-life context are needed. Objective: This study aims to explore whether resting HRV and total sleep time (TST) are indicative and predictive of the within-day accumulation of the negative consequences of stress and mental exhaustion. The tested hypotheses are that demands are positively associated with stress and resting HRV buffers against this association, stress is positively associated with mental exhaustion and resting HRV buffers against this association, stress negatively impacts subsequent-night TST, and previous-evening mental exhaustion negatively impacts resting HRV, while previous-night TST buffers against this association. Methods: In total, 26 interns used consumer-available wearables (Fitbit Charge 2 and Polar H7), a consumer-available smartphone app (Elite HRV), and an ecological momentary assessment smartphone app to collect resilience-related data on resting HRV, TST, and perceived demands, stress, and mental exhaustion on a daily basis for 15 weeks. Results: Multiple linear regression analysis of within-subject standardized data collected on 2379 unique person-days showed that having a high resting HRV buffered against the positive association between demands and stress (hypothesis 1) and between stress and mental exhaustion (hypothesis 2). Stress did not affect TST (hypothesis 3). Finally, mental exhaustion negatively predicted resting HRV in the subsequent morning but TST did not buffer against this (hypothesis 4). Conclusions: To our knowledge, this study provides first evidence that having a low within-subject resting HRV may be both indicative and predictive of the short-term accumulation of the negative effects of stress and mental exhaustion, potentially forming a negative feedback loop. If these findings can be replicated and expanded upon in future studies, they may contribute to the development of automated resilience interventions that monitor daily resting HRV and aim to provide users with an early warning signal when a negative feedback loop forms, to prevent the negative impact of stress on long-term health outcomes.
MULTIFILE
The effects of stress may be alleviated when its impact or a decreased stress-resilience are detected early. This study explores whether wearable-measured sleep and resting HRV in police officers can be predicted by stress-related Ecological Momentary Assessment (EMA) measures in preceding days and predict stress-related EMA outcomes in subsequent days. Eight police officers used an Oura ring to collect daily Total Sleep Time (TST) and resting Heart Rate Variability (HRV) and an EMA app for measuring demands, stress, mental exhaustion, and vigor during 15-55 weeks. Vector Autoregression (VAR) models were created and complemented by Granger causation tests and Impulse Response Function visualizations. Demands negatively predicted TST and HRV in one participant. TST negatively predicted demands, stress, and mental exhaustion in two, three, and five participants, respectively, and positively predicted vigor in five participants. HRV negatively predicted demands in two participants, and stress and mental exhaustion in one participant. Changes in HRV lasted longer than those in TST. Bidirectional associations of TST and resting HRV with stress-related outcomes were observed at a weak-to-moderate strength, but not consistently across participants. TST and resting HRV are more consistent predictors of stress-resilience in upcoming days than indicators of stress-related measures in prior days.
